Safe, Transparent, and Ethical Artificial Intelligence: Keys to Quality Sustainable Education (SDG4)

Francisco José García Peñalvo; Marc Alier; Juanan Pereira; Maria Jose Casany

doi:10.46661/ijeri.11036

Autores/as

Francisco José García Peñalvo Universidad de Salamanca https://orcid.org/0000-0001-9987-5584
Marc Alier UPC Universitat Politècnica de Catalunya https://orcid.org/0000-0003-3922-1516
Juanan Pereira UPV/EHU https://orcid.org/0000-0002-7935-3612
Maria Jose Casany UPC Universitat Politècnica de Catalunya https://orcid.org/0000-0002-5072-6745

DOI:

https://doi.org/10.46661/ijeri.11036

Palabras clave:

Inteligencia Artificial en Educación, AIED, Marco de referencia para una IA segura, Aplicaciones Inteligentes para el Aprendizaje (SLApps), Grandes modelos de lenguaje, Integridad académica e IA

Resumen

La creciente integración de la inteligencia artificial (IA) en los entornos educativos requiere un marco estructurado para garantizar su uso seguro y ético. Se ha propuesto un manifiesto que establece siete principios clave para una IA segura aplicada a la educación, destacando la protección de los datos del estudiantado, la alineación con las estrategias institucionales, la congruencia con las prácticas didácticas, la minimización de errores, interfaces de usuario comprensibles, supervisión humana y transparencia ética. Estos principios están diseñados para guiar la implementación de tecnologías de IA en entornos educativos, abordando riesgos potenciales como violaciones de privacidad, uso indebido y dependencia excesiva de la tecnología. También se introducen las Aplicaciones Inteligentes para el Aprendizaje (SLApps), que integran la IA en el ecosistema tecnológico institucional existente, con especial atención a las plataformas de aprendizaje que son la base de los campus virtuales, permitiendo experiencias de aprendizaje seguras, adaptativas según el rol y específicas para cada asignatura. Si bien los grandes modelos de lenguaje como GPT ofrecen un potencial transformador en la educación, también presentan desafíos relacionados con la precisión, el uso ético y la congruencia pedagógica. Para enfrentar estas complejidades, se recomienda una lista de verificación basada en los principios de IA segura en la educación, que proporciona al profesorado e instituciones un marco para evaluar las herramientas de IA, asegurando que apoyen la integridad académica, mejoren las experiencias de aprendizaje y respeten los estándares éticos.

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